Extending low-code from Spark to SQL fuels Prophecy’s mission to democratize how users derive value from data across the entire business.

Prophecy, the low-code data transformation platform, has announced the release of Prophecy 3.0, expanding beyond low-code Spark for data engineers to provide first-of-its-kind, low-code SQL capabilities for business data users — empowering the entire data organization to self-serve and visually build data products natively on cloud data warehouses. Prophecy 3.0 is now live and available on the Databricks Lakehouse Platform.

“We added low-code SQL to our already robust support for Spark because, over and over, we’ve seen how data analytics and machine learning are bottlenecked when teams can’t feed timely, correct data into their analyses,” shared Prophecy Co-Founder and CEO, Raj Bains. “We built Prophecy 3.0 to empower more team members, across all types of companies, to get faster — and more — value from their business data.”

Continued Bains, “Business data users are the experts for their data but not expert data engineers. So they need tools that will meet them where they are technically, so they can freely explore their data, transform it into meaningful insights and move their changes to production easily, in ways supported by software best practices.”

Prophecy 3.0’s unique technology enables business data users to visually build data pipelines that Prophecy instantly turns into SQL code (as dbt Core™ projects that are 100% open-source). This works in the reverse too – users can open existing dbt Core™ projects in Prophecy, and the SQL is instantly editable as visual pipelines, with the edits saved back as SQL. This will enable the dbt community to invite many more users to collaborate with them in their environment.

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“As enterprises continue to move from on premises to the cloud, data users want to analyze entire datasets using the scale and performance provided by cloud data warehouses. Business data users have used products, such as Alteryx, to visually transform data on-premises, but it cannot use the performance of cloud data warehouses and its proprietary format does not lend itself to collaboration with SQL programmers,” shared Prophecy Co-Founder, Maciej Szpakowski. “On the other hand, relying only on SQL code with dbt Core™ enables a fraction of the business data users, but leaves many others out of the equation. Companies with data users of varying specializations should not have to choose one technology or another – Prophecy 3.0 uniquely provides both unlike any solution previously available through its integrated visual canvas and code editor, making it an indispensable tool for today’s enterprises.”

“As the lakehouse architecture continues to expand, we see Prophecy’s low-code platform as a key technology to enable more data users to benefit from the Databricks Lakehouse Platform,” shared Roger Murff, VP of Technology Partners at Databricks. “Teams across industries will be able to quickly and easily build visual data pipelines with Prophecy to feed data for analytics and machine learning.”

In addition, Prophecy 3.0 continues to meet the demands of existing customers by extending its data engineering capabilities in three key ways: support for Spark Streaming to build real-time data pipelines, low-code for Apache Airflow to simplify data workflow orchestration, and built-in data quality checks to improve pipeline reliability and performance.

Since raising a Series A last year, Prophecy has seen accelerating growth, with enterprises putting their trust in Prophecy’s approach of providing a complete product versus the modern data stack approach of a collection of point solutions for data ingestion, transformation, monitoring, data quality, dataops and metadata, along with separate products for visual and code development. The company has grown its revenue over 600% year over year, closing many six-figure deals with Fortune 500 customers and recently landing its first seven-figure deal from a Fortune 10 leader in healthcare.

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